Development of Plant Reload Optimization Platform Capabilities for Core Design and Fuel Performance Analysis

Choi, Yong-Joon; Abdo, Mohammad; Wang, Congjian; Valeri, Jarrett; Frepoli, Cesare; Nguyen, Khang; Hou, Jason

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https://hdl.handle.net/2142/121836 Copy

Description

Title

Development of Plant Reload Optimization Platform Capabilities for Core Design and Fuel Performance Analysis

Author(s)

• Choi, Yong-Joon
• Abdo, Mohammad
• Wang, Congjian
• Valeri, Jarrett
• Frepoli, Cesare
• Nguyen, Khang
• Hou, Jason

Issue Date

2023

Keyword(s)

• Genetic algorithm
• Plant reload optimization
• Multi-objective optimization

Abstract

The United States (U.S.) Department of Energy (DOE) Light Water Reactor Sustainability (LWRS) Program Risk-Informed Systems Analysis (RISA) Pathway Plant Reload Optimization project aims to develop an integrated, comprehensive platform offering an all-in-one solution for reactor core reload evaluations with a special focus on optimization of core design considering feedback from system safety analysis (i.e., thermal-hydraulics) and fuel performance. The RISA Pathway optimization platform is mainly driven by the Idaho National Laboratory (INL)-developed Risk Analysis and Virtual Environment (RAVEN) computer software which gives unlimited flexibility in using modern artificial intelligence techniques such as Genetic Algorithm (GA). This GA method is a proven technology for fuel reload optimization purpose. RAVEN’s capability is not just limited to optimization. It can also provide input decks to other physical codes and perform post-processing of simulation results. This extensibility of RAVEN facilitates coupling with other physical codes for core design, fuel performance, and systems analysis, which can lead to a unified framework that considers physical phenomena. Hence, using RAVEN as a controller of the GA method allows a “tool-independent” one-stop plant reload optimization platform with easy access for users. The optimization platform can set multiple objectives and constraints such as fuel cycle length (e.g., an extension from 18 to 24 months), fuel enrichment, burnable poisons, core design limits (e.g., peaking factors and boron concentration), safety parameters (e.g., peak cladding temperature and departure of nucleate boiling rate [DNBR]). To do this, the RISA Pathway GA-based optimization platform uses the following individual computational tools coupled with RAVEN to provide safety feedback during core designing: PARCS for core design, RELAP5-3D for system response analysis and TRANSURANUS for fuel performance analysis. This paper summarizes coupling between RAVEN, PARCS, and TRANSURANUS as well as presented demonstrations for verification of the developed GA optimization platform.

Type of Resource

text

Language

eng

Handle URL

https://hdl.handle.net/2142/121836

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